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Gravitational self-lensing in populations of massive black hole binaries

Authors :
Kelley, Luke Zoltan
D'Orazio, Daniel J.
Di Stefano, Rosanne
Kelley, Luke Zoltan
D'Orazio, Daniel J.
Di Stefano, Rosanne
Source :
Kelley , L Z , D'Orazio , D J & Di Stefano , R 2021 , ' Gravitational self-lensing in populations of massive black hole binaries ' , Monthly Notices of the Royal Astronomical Society , vol. 508 , no. 2 , pp. 2524-2536 .
Publication Year :
2021

Abstract

The community may be on the verge of detecting low-frequency gravitational waves from massive black hole binaries (MBHBs), but no examples of binary active galactic nuclei (AGN) have been confirmed. Because MBHBs are intrinsically rare, the most promising detection methods utilize photometric data from all-sky surveys. Gravitational self-lensing has recently been proposed as a method of detecting AGN in close separation binaries. In this study, we calculate the detectability of lensing signatures in realistic populations of simulated MBHBs. Within our model assumptions, we find that VRO's LSST should be able to detect tens to hundreds of self-lensing binaries, with the rate uncertainty depending primarily on the orientation of AGN discs relative to their binary orbits. Roughly a quarter of lensing detectable systems should also show detectable Doppler boosting signatures. If AGN discs tend to be aligned with the orbit, lensing signatures are very nearly achromatic, while in misaligned configurations, the bluer optical bands are lensed more than redder ones. Whether substantial obscuring material (e.g. a dusty torus) will be present in close binaries remains uncertain, but our estimates suggest that a substantial fraction of systems would still be observable in this case.

Details

Database :
OAIster
Journal :
Kelley , L Z , D'Orazio , D J & Di Stefano , R 2021 , ' Gravitational self-lensing in populations of massive black hole binaries ' , Monthly Notices of the Royal Astronomical Society , vol. 508 , no. 2 , pp. 2524-2536 .
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1296098251
Document Type :
Electronic Resource